Poster: MOBS: Multi-operator Observation-Based Slicing Using Lexical Approximation of Program Dependence

ICSE (Companion Volume)(2018)

引用 1|浏览44
暂无评分
摘要
Observation-Based Slicing (ORBS) is a recently introduced program slicing technique based on direct observation of program semantics. Previous ORBS implementations slice a program by iteratively deleting adjacent lines of code. This paper introduces two new deletion operators based on lexical similarity. Furthermore, it presents a generalization of O RBS that can exploit multiple deletion operators: Multi-operator Observation-Based Slicing (MOBS). An empirical evaluation of MOBS using three real world Java projects finds that the use of lexical information, improves the efficiency of ORBS: MOBS can delete up to 87% of lines while taking only about 33% of the execution time with respect to the original ORBS.
更多
查看译文
关键词
Program Slicing,Dependence Analysis,Program Analysis
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要